APPROACH
The solution had four aspects:
- Bringing data from diverse ERP and CRM systems like SAP and Salesforce
- Process, standardize and dedupe the data
- Whitespace identification
- Present the output in an interactive Graph Network
Tredence’s AI/ML based augmented data quality engine Sancus was used to dedupe customer records and a whitespace identification solution was built on top of it to help identify up sell and cross sell opportunities. The solution:
- Cleaned, standardized and deduped customer data coming from different Salesforce systems using proprietary AI/ML algorithms
- Cleaned the product data, and used ML algorithms to create product hierarchies
- Used an advanced recommendation solution to identify whitespaces to boost up sell & cross sell opportunities. This helped the sales team to target the right customer with the appropriate product
- Created a graph network-based visualization that was integrated with Tableau Dashboards so that the sales team could easily interpret the suggestions
KEY BENEFITS
- Entire solution was hosted on AWS ensuring alignment with client’s cloud strategy
- The clean, deduped and standardized Product data helped in improving the accuracy of the recommendation engine
- Deduped customer and product data helped in restructuring of accounts, thus bringing in operation efficiencies
RESULTS